A Fault Diagnosis Method of Temperature Sensor Based on Analytical Redundancy

Fault diagnosis technology of the temperature sensor on the general processing module (GPM) of integrated modular avionics (IMA) was studied. Through the accelerated life testing of the complex programmable logic device (CPLD) on GPM, the corresponding analytical relationship between the oscillator frequency and temperature was obtained, and the analytical redundancy model between temperature and oscillator frequency was constructed. The fault diagnosis algorithm is designed based on statistical hypothesis testing. The moving mean method is used in the alarm process. The paper compares the traditional method WSPRT (Wald Sequential Probability Ratio Test) with MaxSPRT in the verification process. For MaxSPRT, its hypothesis testing model of the normal distribution is deduced. The simulation model of sensor fault is designed. The effectiveness and rapidity of the proposed method are verified.

[1]  Donghua Zhou,et al.  Robust $H_{\infty}$ Filtering for Time-Delay Systems With Probabilistic Sensor Faults , 2009, IEEE Signal Processing Letters.

[2]  Paul M. Frank,et al.  Fault diagnostics and fault tolerant control , 1998 .

[3]  Bin Jiang,et al.  Fault diagnosis and estimation for near-space hypersonic vehicle with sensor faults , 2012, J. Syst. Control. Eng..

[4]  Hong Wang,et al.  On the use of adaptive updating rules for actuator and sensor fault diagnosis , 1997, Autom..

[5]  Gaëtan Kerschen,et al.  Sensor validation using principal component analysis , 2005 .

[6]  Biao Huang,et al.  Detection of abrupt changes of total least squares models and application in fault detection , 2001, IEEE Trans. Control. Syst. Technol..

[7]  M. Kulldorff,et al.  A Maximized Sequential Probability Ratio Test for Drug and Vaccine Safety Surveillance , 2011 .

[8]  Jie Chen,et al.  Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.

[9]  Donghua Zhou,et al.  Active fault-tolerant control of nonlinear batch processes with sensor faults , 2007 .

[10]  Tianhong Zhang,et al.  Analytical Redundancy Design for Aeroengine Sensor Fault Diagnostics Based on SROS-ELM , 2016 .

[11]  Michel Verhaegen,et al.  Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques , 2009 .

[12]  R. Horwitz,et al.  Comparison of epidemiologic data from multiple sources. , 1986, Journal of chronic diseases.

[13]  S. Qin,et al.  Active Fault-Tolerant Control for a Class of Nonlinear Systems with Sensor Faults , 2008 .

[14]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[15]  Zeng Qinghua.  An Improved Sequential Probability Ratio Test Method for Residual Test , 2009 .

[16]  N. Venkateswaran,et al.  Analytical redundancy based fault detection of gyroscopes in spacecraft applications , 2002 .

[17]  Cheng-zhi Chi,et al.  Application of Analytic Redundancy-based Fault Diagnosis of Sensors to Onboard Maintenance System , 2012 .

[18]  Inseok Hwang,et al.  A Survey of Fault Detection, Isolation, and Reconfiguration Methods , 2010, IEEE Transactions on Control Systems Technology.

[19]  Philip T. Krein,et al.  A method for impact assessment of faults on the performance of field-oriented control drives: A first step to reliability modeling , 2010, 2010 Twenty-Fifth Annual IEEE Applied Power Electronics Conference and Exposition (APEC).

[20]  Ian Postlethwaite,et al.  Survey and application of sensor fault detection and isolation schemes , 2011 .

[21]  Xiukun Wei,et al.  Fault estimation of large scale wind turbine systems , 2010, Proceedings of the 29th Chinese Control Conference.

[22]  Massimiliano Mattei,et al.  Nonlinear observers with H∞ performance for sensor fault detection and isolation: a linear matrix inequality design procedure , 2005 .